An intelligent process planning system for micro turn-mill parts

An attempt has been made to develop a generalised system for the generation of process plan for the manufacture of micro parts in this work. It has two components; first one deals with automatic part feature extraction from feature-based model and second one performs the execution of process planning activities in accordance with feature using knowledge-based system approach. The proposed system maps extensible markup language (XML) data for the feature based-model and produces the corresponding manufacturing activities needed for the manufacture of micro parts. The process plan modules considered in this work includes process sequence, tools and fixtures, process parameters selection and set-up plan generation. An attempt has been made to develop process parameters selection module based on experimental investigation and optimisation apart from manufacturing catalogues and user manuals. Feature extraction through XML files avoids complex feature extraction process. The application of the developed system has been verified with a case study. The present system is limited to micro turn-mill features. Incorporation of more micro features and consideration of other activities of process plan ensures a complete process planning system for micro-machining processes.     

A fuzzy approach to process plan selection

Process planning is the systematic determination of the detailed methods by which parts can be manufactured from raw material to finished product. In a real manufacturing environment, usually several different parts need to be manufactured in a single facility sharing constrained resources. The existence of alternative process plans for each part makes the selection of process plan a very important issue in manufacturing. The objectives in process plan selection might be imprecise and conflicting. In this paper, a fuzzy approach is used to deal quantitatively with the imprecision of the process plan selection problem. Each process plan is evaluated and its contribution to shopfloor performance is calculated using fuzzy set theory. A progressive refinement approach is used to first identify the set of process plans that maximize the contributions, and then consolidate the set to reduce the manufacturing resources needed.     

Modular simulation tool for modelling JIT manufacturing

Since quantitative information is very helpful in implementing JIT production techniques, computer simulation can be a valuable tool in designing, implementing or changing JIT practices in a production system. Nowadays, existing simulation software incorporates modular programming and enhanced graphic systems for output representation. It enables users to generate modules that represent partial aspects of a JIT system. These modules, adequately modified and integrated, give researchers and practitioners the possibility to create complex models that can be applied to a variety of JIT systems or JIT production environments. A modular simulation tool, based on the modular capabilities of Witness, is introduced in this paper. As a module example, the feeder double-kanban line module is presented, which represents one of the core aspects of a JIT manufacturing system. Finally, module integration is illustrated by modelling a U-Shaped line. The experimentation and evaluation of the U-line allow one to appreciate how modular simulation can be a powerful tool in decision making, by enabling users to analyse systems configurations and operation rules before implementing them.     

System for early cost estimation of die-cast parts

Early cost estimate of a part is important information and forms a basis for preparing quotations, which are competitive from a market point of view. It is seen that a commonly adopted approach of variant cost estimation based only on geometric information of the component is not always accurate. This is also true in the case of die-cast parts. The geometric complexity of the part, tooling complexity, part and tool material, processing cost, and manufacturing resources for producing the part all need to be considered for accurate cost estimation. This paper deals with a comprehensive system developed to estimate and analyze the manufacturing cost of die-cast parts. A computer-aided cost-estimation system has been developed that applies manufacturing process as well as manufacturing resource considerations in addition to part feature complexity. Use of the proposed system is demonstrated in selecting the optimum number of cavities and the appropriate manufacturing resources under machine-related constraints. Further, the cost-estimation system developed herein is used for carrying out feature sensitivity analysis to identify design features that add significant cost to the part. The use of this system for optimal machine loading in multiple parts situation is also demonstrated.     

Packaging information system

The Packaging Information System is a basic module concerned with the creation of the expert system Risk-Engineering. The structure of this expert system was briefly described in Copenhagen at the IAPRI'92 symposium. It provides information about transport, handling and warehousing needs. The databank of this information system has the following components

• —general regulations
• —specific packaging data
• —specific goods data
• —goods and packaging testing methods

and is used to solve demanding problems, allowing the planner to concentrate on other important assignments. In combination with other modules of the expert system Risk-Engineering, it has at its disposal a range of experience and knowledge of various specialist resources.     

Evaluation of the logistic model of the reconfigurable manufacturing system based on generalised stochastic Petri nets

To reveal the influence on system performance by the logistic model of reconfigurable manufacturing system (RMS), the generalised stochastic Petri nets (GSPN) modular modelling approach is presented in this paper. It is based upon the characteristics of a bottleneck service. According to this approach, the bottleneck service in the production process is found first. By corresponding different resources in the service to different modules of the GSPN, the module is reconfigured. The analysis of the model using the Markov chain is hereby presented, as is the average utilisation factor of RMS. Following this, the production capacity of different products and the average productivity of reconfigurable manufacturing cells (RMCs) are discussed.     

A WWW-based integrated product development platform for sheet metal parts intelligent concurrent design and manufacturing

This paper presents a WWW (World Wide Web) based integrated product development platform for intelligent concurrent design and manufacturing of sheet metal parts. In order to achieve this platform, several major modules are discussed. These modules mainly include the structure of the WWW-based integrated product development platform, an information integration framework, a RTCAPP (real time computer aided process planning) module, a customer interface module, and a design/manufacturing knowledge-based module for supporting product design and manufacturing. This paper gives the structure of the information integration framework for concurrent design and manufacturing of sheet metal parts. An information integration framework, called 'step structure information framework' is proposed. The principles, called 'zero thickness and zero bend radius' are put forward, which can be used to abstract the geometric entities of sheet metal parts in order to facilitate product design and modelling. Finally, case studies are given.     

Agent-based fractal architecture and modelling for developing distributed manufacturing systems

For their timely response to the rapidly changing manufacturing environment and markets, future manufacturing systems must be flexible, adaptable, and reusable. Recently, bionic (or biological), holonic, and fractal manufacturing systems (FrMS) have been discussed as potential candidates for the next generation of manufacturing systems. This study focuses on the FrMS, which is based on the concept of autonomous cooperating agents referred to as fractals. The major component of the FrMS is a basic fractal unit (BFU). It consists of five functional modules: observing module (observer), analysing module (analyser), resolving and executing module (resolver), organizing module (organizer), and reporting module (reporter). Although the FrMS has many conceptual advantages, the implementation of the system has been known to be difficult. This paper is a preliminary study of the basic components and the architecture with an eye toward the future implementation of FrMS. In order to describe the characteristics of a fractal, this paper presents several models including function models using IDEF0, working models using Petri-net, and static/dynamic models using the unified modelling language (UML).     

Improving the performances of part dispatching based on multiple process plans using graph theory

An intrinsic characteristic for manufacturing a part is the existence of diverse processing routes. In this paper, we deal with the improvement of part dispatching performance based on the availability of multiple process plans of a machined part. Procedures to represent multiple process plans with a graphic representation are developed so as to facilitate the utilization of process plans. We propose a simulation model to test the impacts of multiple process plans on the performances of real time scheduling. The study shows that by applying the simulation model to multiple processes in the manufacturing of machined parts, the flexibility of the manufacturing system can be increased; the total production flow time can be reduced; and the efficient utilization of production resources is improved.     

A learning-based methodology for dynamic scheduling in distributed manufacturing systems

To enhance productivity in a distributed manufacturing system under hierarchical control, we develop a framework of dynamic scheduling scheme that explores routeing flexibility and handles uncertainties. We propose a learning-based methodology to extract scheduling knowledge for dispatching parts to machines. The proposed methodology includes three modules: discrete-event simulation, instance generation, and incremental induction. First, a sophisticated simulation module is developed to implement a dynamic scheduling scheme, to generate training examples, and to evaluate the methodology. Second, the search for training examples (good schedules) is successfully fulfilled by the genetic algorithm. Finally, we propose a tolerance-based learning algorithm that does not only acquire general scheduling rules from the training examples, but also adapts to any newly observed examples and thus facilitates knowledge modification. The experimental results show that the dynamic scheduling scheme significantly outperforms the static scheduling scheme with a single dispatching rule in a distributed manufacturing system.     

Integrated and concurrent approach for compound sheet metal cutting and punching

In sheet metal processing and manufacturing, there are a lot of small- and medium-sized job shops. These small- and medium-sized manufacturing companies have been facing keen competitive pressure in the market. This pressure has forced these companies to make every effort to shorten product development lead-time, improve production efficiency, approach high-quality standards, but at the same time cut down the costs. To meet the needs of these companies, this paper presents a compound cutting and punching production method supported by an integrated CAD/CAPP/CAM system in sheet metal manufacturing. Many existing commercial CAD/CAM systems are not suitable for this manufacturing method, especially under concurrent and global design and manufacturing environments. Some problems have to be solved before these CAD/CAM systems can be employed and integrated for this compound manufacturing method. This paper deals mainly with the solutions to solve some of these problems. The solutions include an integrated data integration platform based on Pro/INTRALINK and STEP, and a knowledge-based real time CAPP (RTCAPP) system for compound sheet metal cutting and punching. Within the presented CAD/CAPP/CAM system, some key modules have been developed. They are the automatic tool selection and manufacturing sequencing module, a shortest tool path optimization module, a cost estimation module and an automatic insertion of auxiliary path module based on knowledge bases. These modules will be addressed here.     

Autoclave cure simulation of composite structures applying implicit and explicit FE techniques

Simulation of the autoclave manufacturing technique of composites can yield a preliminary estimation of induced residual thermal stresses and deformations that affect component fatigue life, and required tolerances for assembly. In this paper, an approach is proposed to simulate the autoclave manufacturing technique for unidirectional composites. The proposed approach consists of three modules. The first module is a thermo-chemical model to estimate the temperature and the degree of cure distributions in the composite part during the cure cycle. The second and third modules are a sequential stress analysis using FE-implicit and FE-explicit respectively. User-material subroutine is used to model the viscoelastic properties of the material based on theory of micromechanics.     

An optimal cart moving policy for a flexible manufacturing system

A flexible manufacturing system is composed of many stations such as a load/unload station, a set of workstations, and a common buffer, that are linked together with a material handling system. Each workstation consists of a limited input buffer, a single machine and a limited output buffer. The material handling system consists of a single cart moving parts in the system according to the process paths required by the parts. A part is blocked when it is moved to a workstation but cannot enter the workstation. The function of the common buffer is to temporarily store blocked parts. A blocked part is treated in accordance with a flexible manufacturing system blocking mechanism. We model the flexible manufacturing system by a closed queueing network with the flexible manufacturing system blocking mechanism and a block-dependent static Markov part routing. An optimal cart moving policy that maximizes the expected system throughput is formulated as an undiscounted semi-Markov decision process. Several properties of the optimization problem are characterized. A loop approach is developed for finding an optimal policy. An example is given to illustrate the methodology, and investigate its convergence.     

Production process adapted design of thermoplastic-compatible piezoceramic modules

Fibre-reinforced polymers with thermoplastic matrix systems are suitable for a wide range of applications in the field of function-integrative lightweight structures ready for series production. The development of functional elements which are tailored to processes is therefore of increasingly significant importance. The thermoplastic-compatible piezoceramic modules under development are suitable for adhesive-free integration into fibre-reinforced thermoplastic structures using a welding process which is intrinsic to the manufacturing process. The continuous refinement of the novel module design and the corresponding manufacturing process (which is based on hot-pressing technology) is supported by the development of tailored coupled and physical nonlinear simulation models which facilitate module design and the analysis of functionality in terms of interactions between technical and technological parameters. Special attention is given to the definition of precise, function-specific manufacturing tolerances as well as the residual stresses caused by the various thermal expansion coefficients of the module components and the use thereof as a means of enhancing module performance.     

A structured approach to deadlock detection,avoidance and resolution in flexible manufacturing systems

Production scheduling models that determine part mix ratios and detailed schedules do not usually account for deadlocks that can be caused by part flow. Deadlocks must be prevented for operational control (especially in automated systems). The major thrust of this paper is in developing a structured model for deadlock detection, avoidance and resolution caused by part flow in manufacturing systems. A system status graph can be constructed for the parts currently in the system. Deadlock detection amounts to determining deadlocks in the system status graph. On the other hand, deadlock avoidance amounts to restricting parts movement so that deadlocks are completely avoided in the future. While deadlock detection is a one-step look ahead procedure, deadlock avoidance is a complete look ahead procedure. Deadlock resolution or recovery amounts to judiciously using a limited queue to recover from deadlocks. Deadlock detection and avoidance are absolutely crucial to uninterrupted operation of automated manufacturing systems. A model based in graph theory has been formulated to detect and avoid deadlocks in automated manufacturing systems.     

Guidelines for implementing robust supervisors in flexible manufacturing systems

Over the past several years, researchers have developed numerous control policies that assure deadlock-free operation for flexible manufacturing systems. Using this research base as a foundation, we have developed several supervisory policies that assure robust operation in the face of resource failure. Along with deadlock-free operation, these policies guarantee that failure of unreliable resources does not block production of part types not requiring failed resources. In our previous work, we developed two types of robust policies, those that ‘absorb’ all parts requiring failed resources into the buffer space of failure-dependent resources (resources that support only parts requiring failed resources), and those that ‘distribute’ parts requiring failed resources among the buffer space of shared resources (resources shared by parts requiring and parts not requiring failed resources). These two types of robust controllers assure different levels of robust system operation and impose very different operating dynamics on the system, thus affecting system performance in different ways. In this research, we use extensive simulation and experimentation on a highly complex and configurable system to develop guidelines for choosing the best robust supervisor based on manufacturing system characteristics and performance objectives. We validate these guidelines using seven randomly generated complex systems and find a better than 88% agreement.     

基于UKF模型更新的混合试验方法

在混合试验中,将结构划分为物理子结构和数值子结构两部分。对遭遇强震下大型结构的混合试验,很难保证数值子结构仍处于弹性阶段。为确保数值子结构模型的准确性,提出基于Unscented Kalman filter (UKF) 模型更新混合试验方法。该方法假定数值子结构与物理子结构恢复力模型相同,在混合试验进行中利用物理子结构试验观测数据,采用UKF方法在线识别物理子结构模型参数,实时更新数值子结构模型参数。通过数值模拟,应用UKF方法对单自由度结构非线性模型进行在线参数识别,验证UKF方法性能;通过对弹簧试件实际试验,验证该混合试验方法的有效性。结果表明,基于UKF模型更新混合试验方法较传统混合试验方法精度更高。     

A manufacturing resource allocation method with knowledge-based fuzzy comprehensive evaluation for aircraft structural parts

Manufacturing of aircraft structural parts has the characteristics of multiple varieties, complex structures and small batches, which make the manufacturing resource allocation highly difficult. This paper proposes a manufacturing resource allocation method with knowledge-based fuzzy comprehensive evaluation, considering multiple manufacturing resources including process planners, machine tools and cutting tools, as well as manufacturing process schemes of aircraft structural parts. Knowledge in terms of experts’ experience and historical data is used for fuzzy comprehensive evaluation. A manufacturing resource allocation model is proposed based on the analysis of manufacturing processes of aircraft structural parts. The capability of planners, the complexity of structural parts, the reliability of machine tools, the reliability of cutting tools and the correlations between manufacturing resources and structural parts are evaluated using the fuzzy comprehensive evaluation method. Multiple manufacturing resources are allocated based on the fuzzy comprehensive evaluation results. A prototype system has been implemented and a case study is used to validate the proposed approach.     

Modelling and simulation of manufacturing systems with first-order hybrid Petri nets

First-order hybrid Petri nets are models that consist of continuous places holding fluid, discrete places containing a non-negative integer number of tokens, and transitions, either discrete or continuous. In the first part of the paper, we provide a framework to describe the overall hybrid net behaviour that combines both time-driven and event-driven dynamics. The resulting model is a linear discrete-time, time-varying state variable model that can be directly used by an efficient simulation tool. In the second part of the paper, we focus on manufacturing systems. Manufacturing systems are discrete-event dynamic systems whose number of reachable states is typically very large, hence approximating fluid models have often been used in this context. We describe the net models of the elementary components of a flexible manufacturing system (machines and buffers) and we show in a final example how these modules can be put together in a bottom-up fashion.